An Efficient Anonymous Authentication Scheme Based on Double Authentication Preventing Signature for Mobile Healthcare Crowd Sensing

  • Jinhui Liu
  • Yong YuEmail author
  • Yannan Li
  • Yanqi Zhao
  • Xiaojiang Du
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11449)


With the widespread growth of cloud computing and mobile healthcare crowd sensing (MHCS), an increasing number of individuals are outsourcing their masses of bio-information in the cloud server to achieve convenient and efficient. In this environment, Cloud Data Center (CDC) needs to authenticate masses of information without revealing owners’ sensitive information. However, tremendous communication cost, storage space cost and checking time cost lead to CDC that give rise to all kinds of privacy concerns as well. To mitigate these issues, To mitigate these issues, we propose a data anonymous batch verification scheme for MHCS based on a certificateless double authentication preventing aggregate signature. The proposed scheme can authenticate all sensing bio-information in a privacy preserving way. We then present that the proposed CL-DAPAS scheme is existentially unforgeable in the Random Oracle Model (ROM) assuming that Computational Diffie-Hellman problem is difficult to solve. Furthermore, we provide an implementation and evaluate performance of the proposed scheme and demonstrate that it achieves less efficient computational cost compared with some related schemes.


Mobile healthcare crowd sensing Security Privacy Double authentication preventing signature Elliptic curve discrete logarithm problem 



The author would like to thank the anonymous reviewers for their constructive comments and suggestions. This work was supported by National Key R&D Program of China (2017YFB0802000), National Natural Science Foundation of China (61772326, 61572303, 61872229, 61802239), NSFC Research Fund for International Young Scientists (61750110528), National Cryptography Development Fund during the 13th Five-year Plan Period (MMJJ20170216, MMJJ201701304), Foundation of State Key Laboratory of Information Security (2017-MS-03), Fundamental Research Funds for the Central Universities(GK201702004, GK201803061, 2018CBLY006) and China Postdoctoral Science Foundation (2018M631121).


  1. 1.
    Ganti, R.K., Ye, F., Lei, H.: Mobile crowdsensing: current state and future challenges. IEEE Commun. Mag. 49(11), 32–37 (2011)Google Scholar
  2. 2.
    Pryss, R., Reichert, M., Herrmann, J., Langguth, B., Schlee, W.: Mobile crowd sensing in clinical and psychological trials – a case study. In: IEEE International Symposium on Computer-Based Medical Systems, pp. 23–24 (2015)Google Scholar
  3. 3.
    Liu, J., Cao, H., Li, Q., Cai, F., Du, X., Gui, M.: A large-scale concurrent data Anonymous batch verification scheme for mobile healthcare crowd sensing. IEEE Internet Things J. (2018).
  4. 4.
    Zhang, H., Zhang, Q., Du, X.: Toward vehicle-assisted cloud computing for smartphones. IEEE Trans. Veh. Technol. 12(64), 5610–5618 (2015)Google Scholar
  5. 5.
    Li, J., Chen, X., Chow, S.S.M., Huang, Q., Wong, D.S., Liu, Z.: Multi-authority fine-grained access control with accountability and its application in cloud. J. Netw. Comput. Appl. Scholar
  6. 6.
    Li, T., Li, J., Liu, Z., Li, P., Jia, C.: Differentially private naive bayes learning over multiple data sources. Inf. Sci. 444, 89–104 (2018)MathSciNetGoogle Scholar
  7. 7.
    Yu, Y., et al.: Identity-based remote data integrity checking with perfect data privacy preserving for cloud storage. IEEE Trans. Inf. Forensics Secur. 12(4), 767–778 (2017)Google Scholar
  8. 8.
    Li, Y., Yu, Y., Susilo, W., Min, G., Ni, J., Choo, R.: Fuzzy identity-based data integrity auditing for reliable cloud storage systems. IEEE Trans. Dependable Secur. Comput. 16(1), 72–83 (2019)Google Scholar
  9. 9.
    Yu, Y., Li, Y., Yang, B., Susilo, W., Yang, G., Bai, J.: Attribute-based cloud data integrity auditing for secure outsourced storage. IEEE Trans. Emerg. Top. Comput.
  10. 10.
    Xue, L., Yu, Y., Li, Y., Au, M.H., Du, X., Yang, B.: Efficient attribute-based encryption with attribute revocation for assured data deletion. Inf. Sci. 479, 640–650 (2019)MathSciNetGoogle Scholar
  11. 11.
    He, D., Chan, S., Guizani, M.: User privacy and data trustworthiness in mobile crowd sensing. IEEE Wirel. Commun. 22(1), 28–34 (2015)Google Scholar
  12. 12.
    Gisdakis, S., Giannetsos, T., Papadimitratos, P.: Security, privacy, and incentive provision for mobile crowd sensing systems. IEEE Internet Things J. 3(5), 839–853 (2016)Google Scholar
  13. 13.
    Zhang, K., Ni, J., Yang, K., Liang, X., Ren, J., Shen, X.S.: Security and privacy in smart city applications: challenges and solutions. IEEE Commun. Mag. 55(1), 122–129 (2017)Google Scholar
  14. 14.
    Ni, J., Zhang, K., Yu, Y., Lin, X., Shen, X.S.: Providing task allocation and secure deduplication for mobile crowdsensing via fog computing. IEEE Trans. Dependable Secur. Comput. 1–12 (2018).
  15. 15.
    Xiao, Y., Rayi, V., Sun, B., Du, X., Hu, F., Galloway, M.: A survey of key management schemes in wireless sensor networks. J. Comput. Commun. 30(11–12), 2314–2341 (2007)Google Scholar
  16. 16.
    Du, X., Xiao, Y., Guizani, M., Chen, H.H.: An effective key management scheme for heterogeneous sensor networks. Ad Hoc Netw. 5(1), 24–34 (2007)Google Scholar
  17. 17.
    Du, X., Chen, H.H.: Security in wireless sensor networks. IEEE Wirel. Commun. Mag. 15(4), 60–66 (2008)Google Scholar
  18. 18.
    Du, X., Guizani, M., Xiao, Y., Chen, H.H.: Transactions papers, a routing-driven elliptic curve cryptography based key management scheme for heterogeneous sensor networks. IEEE Trans. Wirel. Commun. 8(3), 1223–1229 (2009)Google Scholar
  19. 19.
    Boneh, D., Gentry, C., Lynn, B., Shacham, H.: Aggregate and verifiably encrypted signatures from bilinear maps. In: Biham, E. (ed.) EUROCRYPT 2003. LNCS, vol. 2656, pp. 416–432. Springer, Heidelberg (2003). Scholar
  20. 20.
    Xiong, H., Guan, Z., Chen, Z., Li, F.: An efficient certificateless aggregate signature with constant pairing computations. Inf. Sci. 219, 225–235 (2013)MathSciNetzbMATHGoogle Scholar
  21. 21.
    Shen, L., Ma, J., Liu, X., Wei, F., Miao, M.: A secure and efficient id-based aggregate signature scheme for wireless sensor networks. IEEE Internet Things J. 4(2), 546–554 (2017)Google Scholar
  22. 22.
    Kumar, P., Kumari, S., Sharma, V., Sangaiah, A.K., Wei, J., Li, X.: A certificateless aggregate signature scheme for healthcare wireless sensor network. Sustain. Comput. Inform. Syst. 18, 80–89 (2018)Google Scholar
  23. 23.
    Zhang, L., Zhang, F.: A new certificateless aggregate signature scheme. Comput. Commun. 32(6), 1079–1085 (2009)MathSciNetGoogle Scholar
  24. 24.
    Deng, J., Xu, C., Wu, H., Dong, L.: A new certificateless signature with enhanced security and aggregation version. Concurr. Comput. Pract. Exp. 28(4), 1124–1133 (2016)Google Scholar
  25. 25.
    Gong, Z., Long, Y., Hong, X., Chen, K.: Two certificateless aggregate signatures from bilinear maps. In: IEEE SNPD 2007, vol. 3, pp. 188–193 (2007)Google Scholar
  26. 26.
    Au, M.H., Yang, G., Susilo, W., Zhang, Y.: (Strong) Multidesignated verifiers signatures secure against rogue key attack. Concurr. Comput. Pract. Exp. 26(8), 1574–1592 (2014)Google Scholar
  27. 27.
    Tu, H., He, D., Huang, B.: Reattack of a certificateless aggregate signature scheme with constant pairing computations. Sci. World J. 2014, 1–9 (2014)Google Scholar
  28. 28.
    Malhi, A.K., Batra, S.: An efficient certificateless aggregate signature scheme for vehicular ad-hoc networks. Discret. Math. Theor. Comput. Sci. 17(1), 317–320 (2015)MathSciNetzbMATHGoogle Scholar
  29. 29.
    Bayat, M., Barmshoory, M., Rahimi, M., Aref, M.R.: A secure authentication scheme for VANETs with batch verification. Wirel. Netw. 21(5), 1–11 (2014)Google Scholar
  30. 30.
    Camenisch, J., Stadler, M.: Efficient group signature schemes for large groups. In: Kaliski, B.S. (ed.) CRYPTO 1997. LNCS, vol. 1294, pp. 410–424. Springer, Heidelberg (1997). Scholar
  31. 31.
    Au, M.H., Liu, J.K., Susilo, W., Yuen, T.H.: Secure id-based linkable and revocable-iff-linked ring signature with constant-size construction. Theory Comput. Sci. 469, 1–14 (2013)MathSciNetzbMATHGoogle Scholar
  32. 32.
    Poettering, B., Stebila, D.: Double-authentication-preventing signatures. In: Kutyłowski, M., Vaidya, J. (eds.) ESORICS 2014, Part I. LNCS, vol. 8712, pp. 436–453. Springer, Cham (2014). Scholar
  33. 33.
    Bellare, M., Poettering, B., Stebila, D.: Deterring certificate subversion: efficient double-authentication-preventing signatures. In: Fehr, S. (ed.) PKC 2017, Part II. LNCS, vol. 10175, pp. 121–151. Springer, Heidelberg (2017). Scholar
  34. 34.
    Boneh, D., Kim, S., Nikolaenko, V.: Lattice-based DAPS and generalizations: self-enforcement in signature schemes. In: Gollmann, D., Miyaji, A., Kikuchi, H. (eds.) ACNS 2017. LNCS, vol. 10355, pp. 457–477. Springer, Cham (2017). Scholar
  35. 35.
    Mao, S., Zhang, P., Wang, H., Zhang, H., Wu, W.: Cryptanalysis of a lattice based key exchange protocol. Sci. China Inf. Sci. 60(2), 028101–028105 (2017)Google Scholar
  36. 36.
    Wu, W., Zhang, H., Wang, H., Mao, S., Wu, S., Han, H.: Cryptanalysis of an MOR cryptosystem based on a finite associative algebra. Sci. China Inf. Sci. 59(3), 32111 (2016)Google Scholar
  37. 37.
    Huang, X., Mu, Y., Susilo, W., Wong, D.S., Wu, W.: Certificateless signatures: new schemes and security models. Comput. J. 55(4), 457–474 (2011)Google Scholar
  38. 38.
    He, D., Zeadally, S., Xu, B., Huang, X.: An efficient identity-based conditional privacy-preserving authentication scheme for vehicular ad hoc networks. IEEE Trans. Inf. Forensics Secur. 10(12), 2681–2691 (2015)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jinhui Liu
    • 1
  • Yong Yu
    • 1
    Email author
  • Yannan Li
    • 2
  • Yanqi Zhao
    • 1
  • Xiaojiang Du
    • 3
  1. 1.School of Computer ScienceShaanxi Normal UniversityXi’anChina
  2. 2.School of Computing and Information TechnologyUniversity of WollongongWollongongAustralia
  3. 3.Department of Computer and Information SciencesTemple UniversityPhiladelphiaUSA

Personalised recommendations